# AI Call & Chat QA Scoring Software | Digisensus > Automatic QA scoring against your rule sets, customer journey timelines, compliance flags, deep-dive audits and data extraction — on every conversation. Conversational intelligence # Your agents pass every review. Your customers still leave. Digisensus scores every call, chat and email — and the whole customer journey between them — so you see an account slipping while it is still yours. [Book a demo](https://calendar.app.google/MM4rtjEa8ctThvoZ8) 100% of conversations scored — not a 2% sample. Voice, chat, email and messaging. CUSTOMER JOURNEY · SARAH MILLER 6 touchpoints · 79 days 6 of 6 conversations passed QA Journey failing Digisensus caught it: the same billing question came back three times across three channels — and was never resolved. Scoring & QA ## Your scorecard. Applied to every single conversation. Criteria, weights, pass/partial/fail definitions — yours. The AI scores against them and backs every score with a quote from the conversation. Reviewers stop listening from zero: they confirm or correct. - Different rule sets per account or team - Every criterion with rationale, recommendation and supporting quote - One-click manual review — traceable and reversible Greeting & identity verification Passed "Good morning, this is Sarah speaking. Could I have your contract number, please?" Resolution confirmation Failed The agent never confirmed the customer's issue was actually resolved before ending the call. RECOMMENDATION Close with a confirmation question — "Did that fully resolve your issue?" — and name the next step if it didn't. TOTAL SCORE 71 And on every conversation, out of the box: Conversation summary Who called, what they wanted, what was promised and how it ended — three sentences instead of a 40-minute recording. Sentiment analysis Customer mood at the start and at the end of the conversation — and whether the agent made it better or worse. Issue resolution Resolved or not — every conversation is tagged, and unresolved issues don't disappear when the ticket closes. Customer journeys ## Tickets close. Journeys fail. Every contact from one customer — calls, emails, chats and system events — on a single timeline with the score arc, sentiment and promises given. A broken promise shows up before the customer asks to cancel. - Promises tracked: kept, pending, broken — with the agent responsible - AI suggestions: what to do — and not do — with this account - Flag a journey for review and assign an owner Onboarding callMar 04 Resolved · Sarah M.96 Billing questionApr 19 Closed · not resolved88 Same question againMay 02 Transferred · promise given84 Asks to cancelMay 21 Promise broken54 AI JOURNEY SUMMARY Risk: high. Billing issue unresolved for 78 days across three channels. Recommended: a manager call within 48 hours. Compliance ## Critical violations surface the same day, not at audit time Arm any rule as critical — a missed mandatory disclosure, a mis-promise, a data-protection slip. One violation blocks sign-off and lands on the dashboard, pinned to the exact second in the recording. Critical violations today 3 Mandatory price disclosure not given Call · 04:31 Refund promised without authority Chat · 11:42 Personal data shared before identity check Call · 00:58 Every violation blocks sign-off until a manager reviews it. Deep-dive audits ## One conversation is an anecdote. Thousands are the picture. Reading thousands of conversations and customer journeys at once surfaces what single-conversation review never can: systematic problems, trends as they emerge, every recurring pain point — and where they repeat. You learn what to fix first, where money is leaking, and what's coming — backed by quotes you can take into a board meeting. AUDITTYPECONVSSTATUS #62Discovery1,846Running · 64% #61Sales312Completed #60Agent evaluation958Completed Default quick-start options at your hand: Discovery Suggests scoring rules, maps agent script and responsibilities, categorizes what customers call about. Customer service RATER scorecard, JTBD clustering, per-agent breakdown, prioritized recommendations. Sales Overview of drivers, per-agent behaviours, suggested call script from what actually worked. Agent evaluation Evaluate a single agent. Progress, competencies, development plan, and optional objective tracking. Deep dive Analyses far more calls than one audit can hold: groups them by theme, distills each group, then synthesises one deep report. Data extraction ## Define what to look for. Get structured data back. Order number, promised date, competitor mention, cancellation reason — describe it in plain language and every conversation returns the value, or an honest null. Promised date Any date the agent committed to 2026-07-30 Competitor mention Another vendor's name, if raised null Cancellation reason Why the customer wants out "price after discount" Audio quality analysis ## Bad audio isn't the agent's fault. But it is your problem. Every call is also measured technically: audio quality per side, dead-air time and speech ratio. A noisy headset, a bad line or long silences show up before they show up in your customer ratings. - Audio quality rated separately for agent and customer - Dead air and agent/customer speech ratio on every call - Violation markers on the waveform — click to jump straight to the moment Audio quality Acceptable AgentExcellent ClientAcceptable Client · Packet loss · 01:12Agent · Echo · 03:48Client · Low volume · 05:21 Violation marker · hover for detail, click to seek 3.9% DEAD AIR 16.4s Agent **78%****22%** Client SPEECH RATIO Cowork ## The assistant that doesn't just answer. It does the work. Cowork controls every feature of the system. It creates scoring rule sets and service standards, reviews evaluations and corrects them, analyzes any data you have — and answers any question along the way. - Creates and edits scoring rule sets and standards - Reviews evaluations and makes corrections - Analyzes any available data, with sources shown Create a new scoring rule set for our bank loans line. DONE · 4 STEPS 12.8s Read 1,246 loan-line conversationsconversations.search Drafted 9 criteria, weighted to 100%rules.create Armed "Mis-stated interest rate" as criticalrules.critical Set as default for the Loans accountsaccounts.update DIGISENSUS Done — "Bank loans — QA v1" is live: 9 criteria weighted to 100%, critical violation armed. Want me to rescore last month against it? SOURCE · 1,246 conversations · Loans line Channels ## One quality standard across every channel Voice calls Live chat Email Messaging ## See it on your own conversations A 30-minute demo. Pick a meeting time slot now. [Book a demo](https://calendar.app.google/MM4rtjEa8ctThvoZ8) --- - Canonical: https://digisensus.com/conversation-intelligence/ - Lithuanian version: https://digisensus.com/lt/pokalbiu-analitika/ - Book a demo: https://calendar.app.google/MM4rtjEa8ctThvoZ8 - Contact: saulius@digisensus.com · +370 620 69969